New composite models for the Danish fire insurance data

In recent years, several composite models based on the lognormal distribution have been developed for the Danish fire insurance data. In this note, we propose new composite models based on the lognormal distribution. At least one of the newly proposed models is shown to give a better fit to the Danish fire insurance data.

[1]  H. Akaike.  A new look at the statistical model identification , 1974 .

[2]  George A. F. Seber,et al.  Linear regression analysis , 1977 .

[3]  Stuart A. Klugman,et al.  Loss Models: From Data to Decisions , 1998 .

[4]  Howard R. Waters,et al.  Loss Models: from Data to Decisions. By Stuart Klugman, Harry Panjer and Gordon Willmot [John Wiley & Sons, New York, 1998] , 1999 .

[5]  Alan J. Lee,et al.  Linear Regression Analysis: Seber/Linear , 2003 .

[6]  Krzysztof Burnecki,et al.  Modeling the Risk Process in the XploRe Computing Environment , 2004, International Conference on Computational Science.

[7]  Malwane M. A. Ananda,et al.  Modeling actuarial data with a composite lognormal-Pareto model , 2005 .

[8]  David P. M. Scollnik.  On composite lognormal-Pareto models , 2007 .

[9]  Christophe Dutang,et al.  actuar: An R Package for Actuarial Science , 2008 .

[10]  P. Müller,et al.  Fitting and Validation of a Bivariate Model for Large Claims , 2008 .

[11]  R. Lillo,et al.  Bayesian estimation of finite time ruin probabilities , 2009 .

[12]  Yoshua Bengio,et al.  A hybrid Pareto model for asymmetric fat-tailed data: the univariate case , 2009 .

[13]  Simon Guillotte,et al.  Non‐parametric Bayesian inference on bivariate extremes , 2009, 0911.3270.

[14]  Peter Dalgaard,et al.  R Development Core Team (2010): R: A language and environment for statistical computing , 2010 .

[15]  Claudia Klüppelberg,et al.  Parameter estimation of a bivariate compound Poisson process , 2010 .

[16]  Arthur Charpentier,et al.  Beta kernel quantile estimators of heavy-tailed loss distributions , 2010, Stat. Comput..